Thinking time

‘Added value’ is close to becoming a research cliché, if indeed it hasn’t already. At the BIG Conference this year, for instance, there was an emphasis on maximising and integrating data, on having the ability to connect different pieces of evidence and present them as a whole. However, very few of these presentations seemed to touch the ‘third rail’ of research: time. In fact, only one presentation did. Caroline Florence, from Royal Mail, declared, ‘we have got to have the time to play around with the data.’

 

As a general rule, agencies increasingly seem to offer additional services – activation days, enrichment workshops, holistic analysis – while at the same time reducing the turnaround time on projects. Obviously there are times when all we want is the data (think tracking data, the latest NPS score, or exits polls), but most of the time, for most projects, there will be a need to sit back and gain some understanding of what the evidence actually means. Yet it’s not unheard of to go from close of fieldwork to final presentation in a mere 24 hour period. But when is there time to think about the results, put them in context, connect the dots as it were and identify the higher concepts? There can’t be, and so any claims to be adding value are, well, dubious at best.

 

It seems as an industry, indeed as a society, we appear to be speeding up – but not necessarily with good reason. It may come as little surprise that Americans work the longest hours of all nations. But did you know that, according to the International Labour Organisation, workers in Belgium, France, and Norway are all more productive per hour than their Americans counterparts? Working less frantically can lead to better results. This forms the premise of Guy Claxton’s book Hare Brain and Tortoise Mind.

 

Claxton argues that there are two types of thinking speeds: Fast and Slow. ‘Fast Thinking is rational, analytical, linear, logical. It is what we do under pressure, when the clock is ticking. It delivers clear solutions to well-defined problems. Slow Thinking is intuitive, woolly and creative. It is what we do when the pressure is off, and we have the time to let ideas simmer at their own pace on the back burner. It yields rich and subtle insights.’ Both are good, but both need each other.

 

The problem is that while Fast Thinking is on the up, Slow Thinking is in decline. Fast Thinking has somehow come to be seen as better – perhaps, though a tad unfairly, off the back of books like Blink! by Malcolm Gladwell. Of course Fast Thinking is important. From a research perspective it allows us to check tables quickly, manage fieldwork efficiently, and pull together results on schedule. But with the increasing demand for faster delivery and shorter turnarounds, are we leaving ourselves enough time to think Slowly? Perhaps not, and this is detrimental.

 

Milan Kundera, the award-winning Czech author, coined the phrase, ‘the wisdom of slowness.’ And it’s not hard to see why. When asked how he discovered gravity, Newton replied, ‘I thought a lot about it.’ Einstein was often found just sitting in his office staring into space. And Charles Darwin described himself as a Slow Thinker. Clearly, then, there is some benefit in Slow Thinking. But it takes time. As Carl Honore explains, ‘relaxation is often a precursor to Slow Thinking. Research shows people think more creatively when they are calm, unhurried and free from stress.’ The problem is that we are speeding up, and as we do so we are becoming more stressed and more reliant on Fast Thinking, and so losing the skills of Slow Thinking.

 

The critical issue, and one highlighted by Florence, is how to emphasise the benefits of Slow Thinking to the client – of explaining just what virtue there is in spending time thinking about the higher meaning of the data. At present, it is easier on the part of the client to pay for the data and do the added value in-house. So we must become better at explaining what added value means, highlighting how our additional services and consultancy skills can help and, most importantly, give the client a reason to believe.

 

This requires a fundamental shift in the way we propose research projects – in terms of providing timetables, costing structures, and outputs that incorporate the provision of both Fast and Slow Thinking. If we want to move away from dumping the data we must stop pricing ourselves in terms of data output and rather in terms of lasting benefit to the client; of the problem solved or the solution identified. As Jeremy Bullmore said, ‘having mined an insight be as insistent as the diamond trade that once out of the earth it be cut and polished and made to glitter and inspire.’

 

All of which takes some Slow Thinking.

 

Patrick Young